A Fractal Approach Towards Visual Analogy

We present a preliminary computational model of visual analogy that uses fractal image representations that rely only on the grayscale pixel values of input images, and are mathematical abstractions quite rigorously grounded in the theory of fractal image compression. We have applied this model of visual analogy to problems from the Raven’s Progressive Matrices intelligence test, and we describe in detail the fractal solution strategy as well as some preliminary results. Finally, we discuss the implications of using these fractal representations for memory recall and analogical reasoning.